We utilized review articles related to manufacturing to find the most frequent and diverse terms since it generally mention most of the past work and technologies developed in the succinct text. Ten full review articles [1]}, [2]}, [3]}, [4]}, [5]}, [6]}, [7]}, [8]}, [9]}, [10]} for this part were selected, which were processed using a trained neural network model consisting of BERT [11]} and GloVe [12]} stacked embeddings through Flair framework [13]}. Next, we employed BiLSTM and CRF [14]} architecture to identify 12 category entities in the review articles with F-score of 83%. Overall, we found about 2000 entities from diverse review articles related to manufacturing.
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